CITATION.cff

cff-version: 1.2.0
message: "If you use this software, please cite the software itself via zenodo as below, plus a CIL article, please see the CIL README for more details: https://github.com/TomographicImaging/CIL"
abstract: >
  The Core Imaging Library (CIL) is an open-source Python framework for tomographic imaging
  with particular emphasis on reconstruction of challenging datasets. Conventional filtered
  backprojection reconstruction tends to be insufficient for highly noisy, incomplete, non-standard
  or multichannel data arising for example in dynamic, spectral and in situ tomography. CIL
  provides an extensive modular optimisation framework for prototyping reconstruction methods
  including sparsity and total variation regularisation, as well as tools for loading, preprocessing
  and visualising tomographic data.
authors:
- family-names: Pasca
  given-names: Edoardo
- family-names: Jørgensen
  given-names: Jakob Sauer
- family-names: Papoutsellis
  given-names: Evangelos
- family-names: Ametova
  given-names: Evelina
- family-names: Fardell
  given-names: Gemma
- family-names: Thielemans
  given-names: Kris
- family-names: Murgatroyd
  given-names: Laura
- family-names: Duff
  given-names: Margaret
- family-names: da Costa-Luis
  given-names: Casper
- family-names: Robarts
  given-names: Hannah
- family-names: Sugic
  given-names: Danica
title: Core Imaging Library (CIL)
date-released: '2018-01-08'
identifiers:
- description: This is the collection of archived snapshots of all versions of the Core Imaging Library
  type: doi
  value: 10.5281/zenodo.4746198
keywords:
- tomographic imaging
- research
- tomography
- reconstruction
- imaging
- hyperspectral
- optimisation
license: Apache-2.0